Abstract
Users of Scientific Computing Environments (SCE) benefit from faster high-level software development at the cost of larger run time due to the interpreted environment. For time-consuming SCE applications, dividing the workload among several computers can be a cost-effective acceleration technique. Using our PVM and MPI toolboxes, Matlab$^{\rm {\sc {\textregistered}}}$ and Octave users in a computer cluster can parallelize their interpreted applications using the native cluster programming paradigm — message-passing. Our toolboxes are complete interfaces to the corresponding libraries, support all the compatible datatypes in the base SCE and have been designed with performance and maintainability in mind. Although in this paper we focus on our new toolbox, MPITB for Octave, we describe the general design of these toolboxes and of the development aids offered to end users, mention some related work, mention speedup results obtained by some of our users and introduce speedup results for the NPB-EP benchmark for MPITB in both SCE's.
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